Top Senior Analysis Reporting Jobs in Dayton, OH

The Lead Data Platform Engineer will design and build Virtuous's data platform, ensuring it is secure, scalable, and AI-ready. Responsibilities include architecting access controls, optimizing performance, and enabling self-service analytics while maintaining governance and compliance standards.

As a Senior GTM Data Scientist, you will develop predictive models, analyze experiments, and provide actionable insights to GTM teams.

The Staff Data Engineer will lead financial data operations, ensuring accuracy and reliability of data pipelines, while collaborating with Finance, Product, and Engineering teams to enhance systems and decision-making processes.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.

Design, develop, and maintain Power BI dashboards and automated reports for financial analytics. Ensure data accuracy, build data models and ETL pipelines, write/optimize SQL and DAX, analyze trends to provide insights, and collaborate with stakeholders to define reporting requirements and best practices.

Contract Tableau expert to design, build, and improve dashboards from source data. Model complex datasets, optimize performance and usability, establish dashboard best practices, and partner with stakeholders to deliver actionable reporting (30–35 hours/week, contractor).

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Design and maintain enterprise revenue-cycle KPIs and dashboards, analyze multi-source RCM datasets, build predictive models, identify process improvements, support audit/compliance, lead stakeholder working groups, author executive deliverables, follow PM best practices, mentor junior analysts, and safeguard PHI/PII under DoD controls.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.